VOLTA: adVanced mOLecular neTwork Analysis

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    Abstract

    Motivation

    Network analysis is a powerful approach to investigate biological systems. It is often applied to study gene co-expression patterns derived from transcriptomics experiments. Even though co-expression analysis is widely used, there is still a lack of tools that are open and customizable on the basis of different network types and analysis scenarios (e.g. through function accessibility), but are also suitable for novice users by providing complete analysis pipelines.
    Results

    We developed VOLTA, a Python package suited for complex co-expression network analysis. VOLTA is designed to allow users direct access to the individual functions, while they are also provided with complete analysis pipelines. Moreover, VOLTA offers when possible multiple algorithms applicable to each analytical step (e.g. multiple community detection or clustering algorithms are provided), hence providing the user with the possibility to perform analysis tailored to their needs. This makes VOLTA highly suitable for experienced users who wish to build their own analysis pipelines for a wide range of networks as well as for novice users for which a ‘plug and play’ system is provided.
    Availability and implementation

    The package and used data are available at GitHub: https://github.com/fhaive/VOLTA and 10.5281/zenodo.5171719.
    Original languageEnglish
    Article number4587-4588
    JournalBioinformatics
    Volume37
    Issue number23
    DOIs
    Publication statusPublished - 2021
    Publication typeA1 Journal article-refereed

    Publication forum classification

    • Publication forum level 3

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